Next Generation Sequencing Analysis of Wastewater Treatment Plant Process via Support Vector Regression

摘要

In this paper，we analyze next generation sequencing (NGS) data of wastewatertreatment plant (WWTP) in the North Water facility for revealing the role of 1236 differentgenera of microorganisms in the aeration basin to the measured process data.Both the time-series data of NGS and process parameters are pre-processed and analyzed using supportvector regression technique and is compared with the deep neural network approach.Localsensitivity analysis is performed on the resulting models.Both machine learning analyses showthe importance of a subset of genera to the wWTP process and can be used to enrich thewell-studied activated sludge model (ASMI).